An ANN-based ward equivalent approach for power system security assessment

被引：2
|
作者：
Chung, T.S. [1 ]
Fu, Ying [1 ]
机构：
[1] Department of Electrical Engineering, Hong Kong Polytechnic University, Hong Kong, Hong Kong
来源：
| 2001年 / Taylor and Francis Ltd卷 / 29期
关键词：
D O I：
10.1080/153250001461183
中图分类号：
学科分类号：
摘要：
This paper presents a novel hybrid Artificial Neural Network (ANN) and extended Ward-type equivalent approach for fast on-line voltage security assessment of power systems. The proposed approach maintains the desirable properties of the Ward equivalent method and can update online the parameters of the equivalent model when the topology of the external system changes. Moreover, fast boundary matching is achieved by using ANN. Test results demonstrate that the new approach is efficient and has good accuracy.
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